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This addresses the issue found by: https://lab.llvm.org/buildbot/#/builders/92/builds/36449
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2.9 KiB
ReStructuredText
83 lines
2.9 KiB
ReStructuredText
===========
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Clang-Repl
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===========
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**Clang-Repl** is an interactive C++ interpreter that allows for incremental
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compilation. It supports interactive programming for C++ in a
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read-evaluate-print-loop (REPL) style. It uses Clang as a library to compile the
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high level programming language into LLVM IR. Then the LLVM IR is executed by
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the LLVM just-in-time (JIT) infrastructure.
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Clang-Repl is suitable for exploratory programming and in places where time
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to insight is important. Clang-Repl is a project inspired by the work in
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`Cling <https://github.com/root-project/cling>`_, a LLVM-based C/C++ interpreter
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developed by the field of high energy physics and used by the scientific data
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analysis framework `ROOT <https://root.cern/>`_. Clang-Repl allows to move parts
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of Cling upstream, making them useful and available to a broader audience.
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Clang-Repl Usage
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================
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.. code-block:: text
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clang-repl> #include <iostream>
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clang-repl> int f() { std::cout << "Hello Interpreted World!\n"; return 0; }
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clang-repl> auto r = f();
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// Prints Hello Interpreted World!
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Note that the implementation is not complete and highly experimental. We do
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not yet support statements on the global scope, for example.
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Clang-Repl Basic Data Flow
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==========================
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.. image:: ClangRepl_design.png
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:align: center
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:alt: ClangRepl design
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Clang-Repl data flow can be divided into roughly 8 phases:
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1. Clang-Repl controls the input infrastructure by an interactive prompt or by
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an interface allowing the incremental processing of input.
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2. Then it sends the input to the underlying incremental facilities in Clang
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infrastructure.
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3. Clang compiles the input into an AST representation.
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4. When required the AST can be further transformed in order to attach specific
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behavior.
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5. The AST representation is then lowered to LLVM IR.
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6. The LLVM IR is the input format for LLVM’s JIT compilation infrastructure.
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The tool will instruct the JIT to run specified functions, translating them
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into machine code targeting the underlying device architecture (eg. Intel
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x86 or NVPTX).
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7. The LLVM JIT lowers the LLVM IR to machine code.
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8. The machine code is then executed.
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Just like Clang, Clang-Repl can be integrated in existing applications as a
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library (via using the clangInterpreter library). This turning your C++ compiler
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into a service which incrementally can consume and execute code. The
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**Compiler as A Service** (**CaaS**) concept helps supporting move advanced use
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cases such as template instantiations on demand and automatic language
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interoperability. It also helps static languages such as C/C++ become apt for
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data science.
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Related Reading
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===============
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`Cling Transitions to LLVM's Clang-Repl <https://root.cern/blog/cling-in-llvm/>`_
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`Moving (parts of) the Cling REPL in Clang <https://lists.llvm.org/pipermail/llvm-dev/2020-July/143257.html>`_
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`GPU Accelerated Automatic Differentiation With Clad <https://arxiv.org/pdf/2203.06139.pdf>`_
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